Fundamentals of algorithms

what is Pseudocode

notation used to describe what an algorithm does

what does an input and output algorithm look like

what does an assignment algorithm look like

what does an If statement algorithm look like

what does an for loop  algorithm look like

what does an while loop  algorithm look like

O(1) Constant time

operation takes the same amount of time regardless of input size

O(log(n)) Logarithmic time 

Time grows logarithmically with input size

O(n) Linear time

time grows proportionally to input size

O(n log(n)) Quasilinear time

Time grows slightly faster than linear 

O(n²) Quadratic time

Time grows quadratical with input size

O(n³) Cubic time

Time grows cubically with input size

O(2n) Exponential time

Time grows exponentially with input size

P(polynomial) 

time complexity is expressed as O(n^k)

for P(polynomial) what is the input size and constant

n is the input size and k is a constant

NP(Non-deterministic Polynomial)

if solution exists correctness can be verified in polynomial time

when is a problem considered NP-Hard

if all NP problems can be reduced to it in polynomial time

NP complete